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Scholarly Knowledge Modelling

The Rexplore team and Springer Nature have launched a new research project with the aim of developing new innovative solutions to support business processes in Springer Nature. This new initiative builds on our previous collaborations which focus on two research directions. The first one is Smart Topic Miner, a web application which uses semantic web technologies to classify scholarly publications on the basis of a very large automatically generated ontology of research areas. This application is being adopted by the Springer Nature Computer Science editorial team to classify proceedings in the LNCS family. The second one is the work of Angelo Salatino, PhD student founded by Springer Nature, who is investigating new methods for the early detection and forecasting of research trends.
The new project will focus on three different strands of research:
– Enhancing Smart Topic Miner to improve its ability of automatically classifying proceedings and extracting valuable metadata from text;
– Carrying out a formal evaluation of Springer Nature’s internal classification of Computer Science topics;
– Developing a recommender system for selecting the most appropriate editorial products for a given scientific venue.

Early detection of research trends: Osborne, F., Salatino, A., and Motta, E. (2016) How are topics born? Understanding the research dynamics preceding the emergence of new areas. PeerJ Preprints 4, e2306v1.

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